mirror of
https://github.com/HumanAIGC-Engineering/gradio-webrtc.git
synced 2026-02-05 01:49:23 +08:00
853d6a06b5
* Add code * add code * add code * Rename messages * rename * add code * Add demo * docs + demos + bug fixes * add code * styles * user guide * Styles * Add code * misc docs updates * print nit * whisper + pr * url for images * whsiper update * Fix bugs * remove demo files * version number * Fix pypi readme * Fix * demos * Add llama code editor * Update llama code editor and object detection cookbook * Add more cookbook demos * add code * Fix links for PR deploys * add code * Fix the install * add tts * TTS docs * Typo * Pending bubbles for reply on pause * Stream redesign (#63) * better error handling * Websocket error handling * add code --------- Co-authored-by: Freddy Boulton <freddyboulton@hf-freddy.local> * remove docs from dist * Some docs typos * more typos * upload changes + docs * docs * better phone * update docs * add code * Make demos better * fix docs + websocket start_up * remove mention of FastAPI app * fastphone tweaks * add code * ReplyOnStopWord fixes * Fix cookbook * Fix pypi readme * add code * bump versions * sambanova cookbook * Fix tags * Llm voice chat * kyutai tag * Add error message to all index.html * STT module uses Moonshine * Not required from typing extensions * fix llm voice chat * Add vpn warning * demo fixes * demos * Add more ui args and gemini audio-video * update cookbook * version 9 --------- Co-authored-by: Freddy Boulton <freddyboulton@hf-freddy.local>
91 lines
2.7 KiB
Python
91 lines
2.7 KiB
Python
import asyncio
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import re
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from dataclasses import dataclass
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from functools import lru_cache
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from typing import AsyncGenerator, Generator, Literal, Protocol
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import numpy as np
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from huggingface_hub import hf_hub_download
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from numpy.typing import NDArray
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class TTSOptions:
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pass
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class TTSModel(Protocol):
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def tts(self, text: str) -> tuple[int, NDArray[np.float32]]: ...
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async def stream_tts(
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self, text: str, options: TTSOptions | None = None
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) -> AsyncGenerator[tuple[int, NDArray[np.float32]], None]: ...
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def stream_tts_sync(
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self, text: str, options: TTSOptions | None = None
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) -> Generator[tuple[int, NDArray[np.float32]], None, None]: ...
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@dataclass
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class KokoroTTSOptions(TTSOptions):
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voice: str = "af_heart"
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speed: float = 1.0
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lang: str = "en-us"
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@lru_cache
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def get_tts_model(model: Literal["kokoro"] = "kokoro") -> TTSModel:
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m = KokoroTTSModel()
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m.tts("Hello, world!")
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return m
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class KokoroTTSModel(TTSModel):
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def __init__(self):
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from kokoro_onnx import Kokoro
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self.model = Kokoro(
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model_path=hf_hub_download("fastrtc/kokoro-onnx", "kokoro-v1.0.onnx"),
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voices_path=hf_hub_download("fastrtc/kokoro-onnx", "voices-v1.0.bin"),
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)
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def tts(
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self, text: str, options: KokoroTTSOptions | None = None
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) -> tuple[int, NDArray[np.float32]]:
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options = options or KokoroTTSOptions()
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a, b = self.model.create(
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text, voice=options.voice, speed=options.speed, lang=options.lang
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)
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return b, a
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async def stream_tts(
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self, text: str, options: KokoroTTSOptions | None = None
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) -> AsyncGenerator[tuple[int, NDArray[np.float32]], None]:
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options = options or KokoroTTSOptions()
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sentences = re.split(r"(?<=[.!?])\s+", text.strip())
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for s_idx, sentence in enumerate(sentences):
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if not sentence.strip():
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continue
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chunk_idx = 0
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async for chunk in self.model.create_stream(
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sentence, voice=options.voice, speed=options.speed, lang=options.lang
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):
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if s_idx != 0 and chunk_idx == 0:
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yield chunk[1], np.zeros(chunk[1] // 7, dtype=np.float32)
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yield chunk[1], chunk[0]
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def stream_tts_sync(
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self, text: str, options: KokoroTTSOptions | None = None
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) -> Generator[tuple[int, NDArray[np.float32]], None, None]:
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loop = asyncio.new_event_loop()
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# Use the new loop to run the async generator
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iterator = self.stream_tts(text, options).__aiter__()
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while True:
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try:
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yield loop.run_until_complete(iterator.__anext__())
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except StopAsyncIteration:
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break
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